The intersection of Computational Linguistics and Language Learning is developing into a separate subfield of computational linguistics, with a range of research questions and applications. Broadly speaking, one can distinguish two broad uses of Natural Language Processing (NLP) in this context:

On the one hand, NLP can be used to analyze learner language, i.e., words, sentences, or texts produced by language learners. This includes the development of NLP techniques for the analysis of learner language by tutoring systems in Intelligent Computer-Assisted Language Learning (ICALL), automated scoring in language testing, as well as the analysis and annotation of learner corpora in support of research on Second Language Acquisition (SLA).

On the other hand, NLP for the analysis of native language can also play an important role in the language learning context. Applications in this second domain support the search for and the enhanced presentation of native language reading material for language learners, they provide targeted access to relevant examples from native language corpora, or they support the generation of exercises, games, and tests based on native language materials.

Where can I find more information?

  • An overview of NLP and Language Learning in general:
    Meurers, D. (2012). "Natural Language Processing and Language Learning". Encyclopedia of Applied Linguistics, edited by Carol A. Chapelle. Blackwell.
  • An overview of NLP in CALL:
    Nerbonne, John (2003). "Natural Language Processing in Computer-Assisted Language Learning". In R. Mitkov (ed.), The Oxford Handbook of Computational Linguistics, Oxford University Press.
  • A detailed historical overview of NLP in CALL:
    Heift, Trude and Mat Schulze (2007). Errors and Intelligence in Computer-Assisted Language Learning: Parsers and Pedagogues. Routledge.

Some related organizations and event series

Betreut von: Detmar Meurers, Tübingen